Kai Olav presented work from the EPEC-project at ECAL 2017 (the European Conference on Artificial Life) last week. The paper, titled "Evolving neural networks with multiple internal models" explores the ability of evolving neural networks to form internal models of multiple objects. Such internal models are believed to be a key to our ability to interact with and make predictions about the different objects we surround ourselves with, both of which are abilities we would like computers and robots to master. The full paper can be accessed here.